/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/*
 * 本代码从官方例子中的 关联规则 直接copy下来的Java代码
 * 在Spark的官方MLLib中的示例中，基本都是下面这样的
 *
 * 创建SparkConf对象，以SparkConf为配置，创建SparkContext
 * 使用SparkContext对象通过外部文件或者列表等创建RDD
 * 使用RDD的转化(transformation)和MLLib所提供的算法库，操作RDD
 * 对RDD进行行动(action)操作或者输出到文件
 * 关闭SparkConf对象
 *
 * 对每个算法的具体了解目前我还差很多，不清楚某些方法的使用，
 * 在官方能看到一些函数的具体使用
 *
 *      http://spark.apache.org/docs/1.6.0/mllib-guide.html
 *
 * 本例运行结果： [a] => [b], 0.8
 */


package MLLib;

// $example on$
import java.util.Arrays;

import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.mllib.fpm.AssociationRules;
import org.apache.spark.mllib.fpm.FPGrowth;
import org.apache.spark.mllib.fpm.FPGrowth.FreqItemset;
// $example off$

import org.apache.spark.SparkConf;

    public class JavaAssociationRulesExample {

    public static void main(String[] args) {

        SparkConf sparkConf = new SparkConf().setAppName("JavaAssociationRulesExample").setMaster("yarn-client");
        JavaSparkContext sc = new JavaSparkContext(sparkConf);

        // $example on$
        JavaRDD<FPGrowth.FreqItemset<String>> freqItemsets = sc.parallelize(Arrays.asList(
                new FreqItemset<String>(new String[] {"a"}, 15L),
                new FreqItemset<String>(new String[] {"b"}, 35L),
                new FreqItemset<String>(new String[] {"a", "b"}, 12L)
        ));

        AssociationRules arules = new AssociationRules()
                .setMinConfidence(0.8);
        JavaRDD<AssociationRules.Rule<String>> results = arules.run(freqItemsets);

        for (AssociationRules.Rule<String> rule : results.collect()) {
            System.out.println(
                    rule.javaAntecedent() + " => " + rule.javaConsequent() + ", " + rule.confidence());
        }
        // $example off$
    }
}